AIML- Machine Learning Engineer, Machine Learning Platform Technologies
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Do you want to make Apple products more intelligent for our users? The Information Intelligence Infrastructure team is building groundbreaking technology for search, natural language processing, artificial intelligence and machine learning. Our infrastructure is the back-bone of Apple Intelligence. It powers the largest Apple foundation models on servers and a wide gamut of services at Apple including Apple Search, Apple Music, AppleTV, AppStore, iMessages, Photos & Camera, Spotlight, Safari, Siri and upcoming ever exciting Apple products serving millions of queries every day with incredible low latencies, drawing every ounce of compute from our hardware.
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Description
Build the dataset intelligence layer behind Apple-scale foundation models: data mining, information extraction, dataset curation, and evaluation signal that helps models improve faster with less compute. You'll operate at petabyte/trillion-record scale and partner directly with foundation model researchers to turn model failures into targeted data interventions. form the backbone of Apple's search and foundation model platforms.
As part of this team, you will own services, pipeline end-to-end-from initial design and architecture, through implementation, deployment, and long-term operation. You'll collaborate closely with Foundation Model research teams to optimize for cutting-edge model quality improvements.","responsibilities":"Design scalable data mining + information extraction systems over trillions of records to produce training corpora and high-signal subsets.
Build data quality loops - automatic filtering, algorithmic selection, and apply strategies tied to model evaluation outcomes.
Partner with Foundation model research to curate datasets for new architectures; ship production solutions powering real products.
Design, build, and operate large-scale distributed services that power Apple's search and foundation model platforms.
Build and evolve petabyte-scale data pipelines and feature pipelines and serve models.
Define and uphold SLAs for critical services & pipelines , driving reliability, performance, and capacity planning for billions of daily requests.
Collaborate with cross-functional partners (research, engineering, program management, privacy, security) to design solutions that meet user, business, and regulatory requirements.
Improve the overall engineering quality bar through technical reviews, mentoring, documentation, and best practices in testing and observability.
Preferred Qualifications
Experience with training-data curation, synthetic data strategies, or evaluation dataset filtering / subset selection.
MLOps from research prototype → production.
Familiarity with large-model serving/optimization stacks (TensorRT-LLM, vLLM, Triton)
Experience with data-intensive systems (e.g., large-scale data pipelines, feature generation, Dataflow, Spark, Airflow, Dataflow).
Minimum Qualifications
PhD or MS in ML/CS or related with 10+ years of experience.
Strong ML/DL development + evaluation experience; strong coding in Python/Scala/Java; large-scale data processing.
Proficiency in at least one modern programming language Python, Go, or Scala, with a focus on writing robust, maintainable code.
Proficiency in at least one popular ML framework such as PyTorch, TensorFlow, JAX and an understanding of how ML/AI systems are deployed in production.
Familiarity with cloud - Kubernetes, GCP, AWS, Object stores.
Excellent collaboration and communication skills; able to work independently and cross-functionally with research, product, and operations teams.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion
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